000			01907nam a22002057a 4500
005			20260910103720.0
008			260910s2024 |||||||| |||| 00| 0 eng d
020			_a9781032487960
040			_cPK-LaUMT
082			_aT 006.31 _bMEE-D
100	1		_aMeedeniya, Dulani _915447
245	1	0	_aDeep learning : _ba beginners' guide / _cDulani Meedeniya
260			_aBoca Raton : _bCRC Press, _c2024
300			_axiv, 184 p.
500			_aIncludes bibliographical references and index.
520			_a"This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising. The design of the DL models based on artificial neural networks is influenced by the structure and operation of the brain. This book presents a comprehensive resource for those who seek a solid grasp of the techniques in DL. Key features: Provides knowledge on theory and design of state-of-the-art deep learning models for real-world applications Explains the concepts and terminology in problem-solving with deep learning Explores the theoretical basis for major algorithms and approaches in deep learning Discusses the enhancement techniques of deep learning models Identifies the performance evaluation techniques for deep learning models Accordingly, the book covers the entire process flow of deep learning by providing awareness of each of the widely used models. This book can be used as a beginners’ guide where the user can understand the associated concepts and techniques. This book will be a useful resource for undergraduate and postgraduate students, engineers, and researchers, who are starting to learn the subject of deep learning."-- Provided by publisher
546			_aEng
650			_aDeep learning (Machine learning) _913485
942			_cBK
999			_c142481 _d142481